What is Ranet OLAP
Any business that works in current economic conditions needs proper data analysis in order to boost its competitiveness. Efficient data analysis of every business process helps to see correlations between decisions and consequences that affect business.
OLAP is a method of data analysis and data representation that forms information into a multidimensional cube. This form helps better understand and process any amount of information.
Ranet OLAP is a rich business tool that provides users with a broad range of OLAP functions. Ranet OLAP tool is used for all the OLAP data analysis actions. It has a wide range of user-oriented and technical features:

Rapid data process. OLAP cube allows to change data and see changes instantly. This feature is also used for what-if analysis;

Object-oriented architecture. Users work with objects they understand: product, buyer, price. Via these objects they interact with data;

Easy and clear interface and built-in tools that don't demand programming skills. Create customizable reports right in the app using built-in reports manager;

OLAP cube is also used as a data warehouse. First it collects data from any data source - Ranet OLAP was designed to work perfectly with popular databases as Microsoft SQL, Pentaho Mondrian, icCube etc. After that OLAP data cube becomes an independent data source for pivot tables;

Flexible filters to arrange OLAP data in tables to understand and demonstrate information;

Rich dashboard of tools for data visualization.

These and more features make Ranet OLAP a powerfull and user-friendly tool for OLAP data analysis.

Pivot Table
Sorting option in the pivot table; sorting visualization
DrillThrough. Option to export DrillThrough results to Excel
Context menu for cells; option to copy cells in the clipboard, view cell properties
"Build Filter Axis" command that adds elements to the filters area based on the selected cells' rows and columns
"Leave Current Structure" command that filters the pivot table based on selected cells' rows and columns
Pivot Charts
Pie charts for pivot table data visualization
Option to view series on separate charts, customize chart table
Support of the main pivot table actions in the charts
Option to show an additional axis on the chart
Member Choice
New Member Choice filter applicable to levels
Option to view only selected elements
Option to view cube member properties
Element search
Active Filters
Horizontal scrolling in the Active filters area
Export/Import
Report export to / import from the user's computer (XML)
Report export to URL; opening report via URL
Toolbar
Reset button on the Toolbar resets custom calculations and styles
Server Side
XML comments to the server code
Comments to Angular and JavaScript code
Server logic virtual methods for pivot table integration into other applications
Server DLL versioning
Design and Usability
New design
New dialog window for extension customization
Botton toolbar for managing multi-page reports
Report header and footer customization; header/footer export to Excel
Other
Option to modify sizes of all modal windows
Selected elements tree normalization. When the cube structure is changed the saved reports are kept operational
Wrong filter description in the Active filters area
Error executing MDX request when creating custom calculated elements with members from the "Non-empty behavior" editor
Error exporting report to Excel when there is no Rows or Columns area in the pivot table
Error in the pivot table after "Drilldown with the parent"
Error when sorting MDX query execution result in case there are the same elements in Rows or Columns
Error generating MDX query when a single member is selected in the Member Choice
Error recording history when there are filters applied to the report
Error when loading a report with saved user actions
TreeView opens closed nodes when adding/deleting elements
Error displaying the chart when there are negative values in the data source

Data visualization is a set of methods of graphical representation of experimental or other data. It enables users to extract significant information from the pool quicker. Data visualization uses such tools as info graphics, schemata, tables etc. It enables experts in different areas of knowledge or activity to do data analysis more efficiently. Especially it is important for specialists who take part in a decision-making process. It also can be useful for people who deal with Big Data containing a vast amount of multifarious content. Data visualization allows doing an in-depth analysis of details.
Speaking of data visualization tools, it is worth mentioning Ranet Analytics tool. It is some kind of business intelligence software. It offers a diversified content in the form of animation, vector graphics, and others.
Ranet Analytics open up the following opportunities:
· Creation of ad hoc reports
· Using pivot tables
· Preparation of OLAP reports
· Implementation of in-memory analytics
Ranet OLAP services allow developers to design successful business intelligence applications. A built-in framework enables to analyze business performance indicators by means of dashboards and reports.
As you can see from above it is more efficient to work with visualized data than text ones. Data visualization can facilitate such activities as monitoring of market changes, customer preferences, analysis and control of the business situation, finding necessary information and the process of decision-making.